Search engine

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A search engine is a software system that provides hyperlinks to web pages and other relevant information on the Web in response to a user's query. The user inputs a query within a web browser or a mobile app, and the search results are often a list of hyperlinks, accompanied by textual summaries and images. Users also have the option of limiting the search to a specific type of results, such as images, videos, or news.

For a search provider, its engine is part of a distributed computing system that can encompass many data centers throughout the world. The speed and accuracy of an engine's response to a query is based on a complex system of indexing that is continuously updated by automated web crawlers. This can include data mining the files and databases stored on web servers, but some content is not accessible to crawlers.

There have been many search engines since the dawn of the Web in the 1990s, but

, has thus largely focused on Google.

History

Timeline (full list)

Year	Engine	Current status
1993	W3Catalog	Inactive
	ALIWEB	Inactive
	JumpStation	Inactive
	WWW Worm	Inactive
1994	WebCrawler	Active
	Go.com	Inactive, redirects to Disney
	Lycos	Active
	Infoseek	Inactive, redirects to Disney
1995	Yahoo! Search	Active, initially a search function for Yahoo! Directory
	Daum	Active
	Search.ch	Active
	Magellan	Inactive
	Excite	Active
	MetaCrawler	Active
	AltaVista	Inactive, acquired by Yahoo! in 2003, since 2013 redirects to Yahoo!
1996	RankDex	Inactive, incorporated into Baidu in 2000
	Dogpile	Active
	HotBot	Inactive (used Inktomi search technology)
	Ask Jeeves	Active (rebranded ask.com)
1997	AOL NetFind	Active (rebranded AOL Search since 1999)
	goo.ne.jp	Active
	Northern Light	Inactive
	Yandex	Active
1998	Google	Active
	Ixquick	Active as Startpage.com
	MSN Search	Active as Bing
	empas	Inactive (merged with NATE)
1999	AlltheWeb	Inactive (URL redirected to Yahoo!)
	GenieKnows	Inactive, rebranded Yellowee (was redirecting to justlocalbusiness.com)
	Naver	Active
	Teoma	Inactive (redirect to Ask.com)
2000	Baidu	Active
	Exalead	Inactive
	Gigablast	Inactive
2001	Kartoo	Inactive
2003	Info.com	Active
2004	A9.com	Inactive
	Clusty	Inactive (redirect to DuckDuckGo)
	Mojeek	Active
	Sogou	Active
2005	SearchMe	Inactive
	KidzSearch	Active, Google Search
2006	Soso	Inactive, merged with Sogou
	Quaero	Inactive
	Search.com	Active
	ChaCha	Inactive
	Ask.com	Active
	Live Search	Active as Bing, rebranded MSN Search
2007	wikiseek	Inactive
	Sproose	Inactive
	Wikia Search	Inactive
	Blackle.com	Active, Google Search
2008	Powerset	Inactive (redirects to Bing)
	Picollator	Inactive
	Viewzi	Inactive
	Boogami	Inactive
	LeapFish	Inactive
	Forestle	Inactive (redirects to Ecosia)
	DuckDuckGo	Active
	TinEye	Active
2009	Bing	Active, rebranded Live Search
	Yebol	Inactive
	Scout (Goby)	Active
	NATE	Active
	Ecosia	Active
	Startpage.com	Active, sister engine of Ixquick
2010	Blekko	Inactive, sold to IBM
	Cuil	Inactive
	Yandex (English)	Active
	Parsijoo	Active
2011	YaCy	Active, P2P
2012	Volunia	Inactive
2013	Qwant	Active
2014	Egerin	Active, Kurdish / Sorani
	Swisscows	Active
	Searx	Active
2015	Yooz	Inactive
	Cliqz	Inactive
2016	Kiddle	Active, Google Search
2017	Presearch	Active
2018	Kagi	Active
2020	Petal	Active
2021	Brave Search	Active
	Queye	Active
	You.com	Active

In 1945, Vannevar Bush described an information retrieval system that would allow a user to access a great expanse of information, all at a single desk.^[3] He called it a memex. He described the system in an article titled "As We May Think" that was published in The Atlantic Monthly.^[4] The memex was intended to give a user the capability to overcome the ever-increasing difficulty of locating information in ever-growing centralized indices of scientific work. Vannevar Bush envisioned libraries of research with connected annotations, which are similar to modern hyperlinks.^[5]

Link analysis eventually became a crucial component of search engines through algorithms such as Hyper Search and PageRank.^[6][7]

The first internet search engines predate the debut of the Web in December 1990:

Prior to September 1993, the

The first tool used for searching content (as opposed to users) on the

Archie Search Engine

did not index the contents of these sites since the amount of data was so limited it could be readily searched manually.

The rise of

" are characters in the series, thus referencing their predecessor.

In the summer of 1993, no search engine existed for the web, though numerous specialized catalogs were maintained by hand. Oscar Nierstrasz at the University of Geneva wrote a series of Perl scripts that periodically mirrored these pages and rewrote them into a standard format. This formed the basis for W3Catalog, the web's first primitive search engine, released on September 2, 1993.^[18]

In June 1993, Matthew Gray, then at

of the existence at each site of an index file in a particular format.

the crawler encountered.

One of the first "all text" crawler-based search engines was WebCrawler, which came out in 1994. Unlike its predecessors, it allowed users to search for any word in any web page, which has become the standard for all major search engines since. It was also the search engine that was widely known by the public. Also, in 1994, Lycos (which started at Carnegie Mellon University) was launched and became a major commercial endeavor.

The first popular search engine on the Web was

It became one of the most popular ways for people to find web pages of interest, but its search function operated on its web directory, rather than its full-text copies of web pages.

Soon after, a number of search engines appeared and vied for popularity. These included

. Information seekers could also browse the directory instead of doing a keyword-based search.

In 1996,

search engine, which was founded by him in China and launched in 2000.

In 1996, Netscape was looking to give a single search engine an exclusive deal as the featured search engine on Netscape's web browser. There was so much interest that instead, Netscape struck deals with five of the major search engines: for $5 million a year, each search engine would be in rotation on the Netscape search engine page. The five engines were Yahoo!, Magellan, Lycos, Infoseek, and Excite.^[30][31]

]

Search engines were also known as some of the brightest stars in the Internet investing frenzy that occurred in the late 1990s.[32] Several companies entered the market spectacularly, receiving record gains during their initial public offerings. Some have taken down their public search engine and are marketing enterprise-only editions, such as Northern Light. Many search engine companies were caught up in the dot-com bubble, a speculation-driven market boom that peaked in March 2000.

Around 2000,

.

By 2000,

and AltaVista) in 2003. Yahoo! switched to Google's search engine until 2004, when it launched its own search engine based on the combined technologies of its acquisitions.

).

Microsoft's rebranded search engine,

Yahoo! Search

would be powered by Microsoft Bing technology.

As of 2019,[update] active search engine crawlers include those of Google, Sogou, Baidu, Bing, Gigablast, Mojeek, DuckDuckGo and Yandex.

A search engine maintains the following processes in near real time:^[34]

1. Web crawling
2. Indexing
3. Searching^[35]

Web search engines get their information by

Indexing means associating words and other definable tokens found on web pages to their domain names and HTML-based fields. The associations are made in a public database, made available for web search queries. A query from a user can be a single word, multiple words or a sentence. The index helps find information relating to the query as quickly as possible.^[35] Some of the techniques for indexing, and caching are trade secrets, whereas web crawling is a straightforward process of visiting all sites on a systematic basis.

Between visits by the spider, the

.

Typically when a user enters a

showing the context of the keywords matched. These are only part of the processing each search results web page requires, and further pages (next to the top) require more of this post-processing.

Beyond simple keyword lookups, search engines offer their own GUI- or command-driven operators and search parameters to refine the search results. These provide the necessary controls for the user engaged in the feedback loop users create by filtering and weighting while refining the search results, given the initial pages of the first search results. For example, from 2007 the Google.com search engine has allowed one to filter by date by clicking "Show search tools" in the leftmost column of the initial search results page, and then selecting the desired date range.

where the research involves using statistical analysis on pages containing the words or phrases you search for.

The usefulness of a search engine depends on the

" by analyzing texts it locates. This first form relies much more heavily on the computer itself to do the bulk of the work.

Most Web search engines are commercial ventures supported by advertising revenue and thus some of them allow advertisers to have their listings ranked higher in search results for a fee. Search engines that do not accept money for their search results make money by running search related ads alongside the regular search engine results. The search engines make money every time someone clicks on one of these ads.^[39]

Local search is the process that optimizes the efforts of local businesses. They focus on change to make sure all searches are consistent. It is important because many people determine where they plan to go and what to buy based on their searches.^[40]

As of January 2022,^[update]

Graphs are unavailable due to technical issues. Updates on reimplementing the Graph extension, which will be known as the Chart extension, can be found on Phabricator and on MediaWiki.org.

Russia and East Asia

This section needs to be updated. Please help update this article to reflect recent events or newly available information. (December 2023)

In Russia,

]

Europe

Most countries' markets in the European Union are dominated by Google, except for the

The search engine Qwant is based in Paris, France, where it attracts most of its 50 million monthly registered users from.

Although search engines are programmed to rank websites based on some combination of their popularity and relevancy, empirical studies indicate various political, economic, and social biases in the information they provide

is illegal.

Biases can also be a result of social processes, as search engine algorithms are frequently designed to exclude non-normative viewpoints in favor of more "popular" results.[52] Indexing algorithms of major search engines skew towards coverage of U.S.-based sites, rather than websites from non-U.S. countries.^[49]

is one example of an attempt to manipulate search results for political, social or commercial reasons.

Several scholars have studied the cultural changes triggered by search engines,

Customized results and filter bubbles

There has been concern raised that search engines such as Google and Bing provide customized results based on the user's activity history, leading to what has been termed echo chambers or filter bubbles by Eli Pariser in 2011.^[57] The argument is that search engines and social media platforms use algorithms to selectively guess what information a user would like to see, based on information about the user (such as location, past click behaviour and search history). As a result, websites tend to show only information that agrees with the user's past viewpoint. According to Eli Pariser users get less exposure to conflicting viewpoints and are isolated intellectually in their own informational bubble. Since this problem has been identified, competing search engines have emerged that seek to avoid this problem by not tracking or "bubbling" users, such as DuckDuckGo. However many scholars have questioned Pariser's view, finding that there is little evidence for the filter bubble.^[58][59][60] On the contrary, a number of studies trying to verify the existence of filter bubbles have found only minor levels of personalisation in search,^[60] that most people encounter a range of views when browsing online, and that Google news tends to promote mainstream established news outlets.^[61][59]

The global growth of the Internet and electronic media in the

While lack of investment and slow pace in technologies in the Muslim world has hindered progress and thwarted success of an Islamic search engine, targeting as the main consumers Islamic adherents, projects like Muxlim (a Muslim lifestyle site) received millions of dollars from investors like Rite Internet Ventures, and it also faltered. Other religion-oriented search engines are Jewogle, the Jewish version of Google,^[63] and Christian search engine SeekFind.org. SeekFind filters sites that attack or degrade their faith.^[64]

Web search engine submission is a process in which a webmaster submits a website directly to a search engine. While search engine submission is sometimes presented as a way to promote a website, it generally is not necessary because the major search engines use web crawlers that will eventually find most web sites on the Internet without assistance. They can either submit one web page at a time, or they can submit the entire site using a

of a web site as search engines are able to crawl a well designed website. There are two remaining reasons to submit a web site or web page to a search engine: to add an entirely new web site without waiting for a search engine to discover it, and to have a web site's record updated after a substantial redesign.

Some search engine submission software not only submits websites to multiple search engines, but also adds links to websites from their own pages. This could appear helpful in increasing a website's ranking, because external links are one of the most important factors determining a website's ranking. However, John Mueller of Google has stated that this "can lead to a tremendous number of unnatural links for your site" with a negative impact on site ranking.^[65]

In comparison to search engines, a social bookmarking system has several advantages over traditional automated resource location and classification software, such as search engine

), and both need technical countermeasures to try to deal with this.

This article or section may need to be cleaned up or summarized because it has been split from/to Search engine technology#Web search engines .

The first web search engine was Archie, created in 1990^[67] by Alan Emtage, a student at McGill University in Montreal. The author originally wanted to call the program "archives", but had to shorten it to comply with the Unix world standard of assigning programs and files short, cryptic names such as grep, cat, troff, sed, awk, perl, and so on.

The primary method of storing and retrieving files was via the File Transfer Protocol (FTP). This was (and still is) a system that specified a common way for computers to exchange files over the Internet. It works like this: Some administrator decides that he wants to make files available from his computer. He sets up a program on his computer, called an FTP server. When someone on the Internet wants to retrieve a file from this computer, he or she connects to it via another program called an FTP client. Any FTP client program can connect with any FTP server program as long as the client and server programs both fully follow the specifications set forth in the FTP protocol.

Initially, anyone who wanted to share a file had to set up an FTP server in order to make the file available to others. Later, "anonymous" FTP sites became repositories for files, allowing all users to post and retrieve them.

Even with archive sites, many important files were still scattered on small FTP servers. These files could be located only by the Internet equivalent of word of mouth: Somebody would post an e-mail to a message list or a discussion forum announcing the availability of a file.

Archie changed all that. It combined a script-based data gatherer, which fetched site listings of anonymous FTP files, with a regular expression matcher for retrieving file names matching a user query. (4) In other words, Archie's gatherer scoured FTP sites across the Internet and indexed all of the files it found. Its regular expression matcher provided users with access to its database.^[68]

In 1993, the University of Nevada System Computing Services group developed Veronica.^[67] It was created as a type of searching device similar to Archie but for Gopher files. Another Gopher search service, called Jughead, appeared a little later, probably for the sole purpose of rounding out the comic-strip triumvirate. Jughead is an acronym for Jonzy's Universal Gopher Hierarchy Excavation and Display, although, like Veronica, it is probably safe to assume that the creator backed into the acronym. Jughead's functionality was pretty much identical to Veronica's, although it appears to be a little rougher around the edges.^[68]

The World Wide Web Wanderer, developed by Matthew Gray in 1993^[69] was the first robot on the Web and was designed to track the Web's growth. Initially, the Wanderer counted only Web servers, but shortly after its introduction, it started to capture URLs as it went along. The database of captured URLs became the Wandex, the first web database.

Matthew Gray's Wanderer created quite a controversy at the time, partially because early versions of the software ran rampant through the Net and caused a noticeable netwide performance degradation. This degradation occurred because the Wanderer would access the same page hundreds of times a day. The Wanderer soon amended its ways, but the controversy over whether robots were good or bad for the Internet remained.

In response to the Wanderer, Martijn Koster created Archie-Like Indexing of the Web, or ALIWEB, in October 1993. As the name implies, ALIWEB was the HTTP equivalent of Archie, and because of this, it is still unique in many ways.

ALIWEB does not have a web-searching robot. Instead, webmasters of participating sites post their own index information for each page they want listed. The advantage to this method is that users get to describe their own site, and a robot does not run about eating up Net bandwidth. The disadvantages of ALIWEB are more of a problem today. The primary disadvantage is that a special indexing file must be submitted. Most users do not understand how to create such a file, and therefore they do not submit their pages. This leads to a relatively small database, which meant that users are less likely to search ALIWEB than one of the large bot-based sites. This Catch-22 has been somewhat offset by incorporating other databases into the ALIWEB search, but it still does not have the mass appeal of search engines such as Yahoo! or Lycos.^[68]

Excite, initially called Architext, was started by six Stanford undergraduates in February 1993. Their idea was to use statistical analysis of word relationships in order to provide more efficient searches through the large amount of information on the Internet. Their project was fully funded by mid-1993. Once funding was secured. they released a version of their search software for webmasters to use on their own web sites. At the time, the software was called Architext, but it now goes by the name of Excite for Web Servers.^[68]

Excite was the first serious commercial search engine which launched in 1995.^[70] It was developed in Stanford and was purchased for $6.5 billion by @Home. In 2001 Excite and @Home went bankrupt and InfoSpace bought Excite for $10 million.

Some of the first analysis of web searching was conducted on search logs from Excite^[71][72]

In April 1994, two Stanford University Ph.D. candidates,

Their official explanation for the name choice was that they considered themselves to be a pair of yahoos.

As the number of links grew and their pages began to receive thousands of hits a day, the team created ways to better organize the data. In order to aid in data retrieval, Yahoo! (www.yahoo.com) became a searchable directory. The search feature was a simple database search engine. Because Yahoo! entries were entered and categorized manually, Yahoo! was not really classified as a search engine. Instead, it was generally considered to be a searchable directory. Yahoo! has since automated some aspects of the gathering and classification process, blurring the distinction between engine and directory.

The Wanderer captured only URLs, which made it difficult to find things that were not explicitly described by their URL. Because URLs are rather cryptic to begin with, this did not help the average user. Searching Yahoo! or the Galaxy was much more effective because they contained additional descriptive information about the indexed sites.

At Carnegie Mellon University during July 1994, Michael Mauldin, on leave from CMU, developed the Lycos search engine.

Search engines on the web are sites enriched with facility to search the content stored on other sites. There is difference in the way various search engines work, but they all perform three basic tasks.^[73]

1. Finding and selecting full or partial content based on the keywords provided.
2. Maintaining index of the content and referencing to the location they find
3. Allowing users to look for words or combinations of words found in that index.

The process begins when a user enters a query statement into the system through the interface provided.

Type	Example	Description
Conventional	librarycatalog	Search by keyword, title, author, etc.
Text-based	Google, Bing, Yahoo!	Search by keywords. Limited search using queries in natural language.
Voice-based	Google, Bing, Yahoo!	Search by keywords. Limited search using queries in natural language.
Multimedia search	QBIC, WebSeek, SaFe	Search by visual appearance (shapes, colors,..)
Q/A	Stack Exchange, NSIR	Search in (restricted) natural language
Clustering Systems	Vivisimo, Clusty
Research Systems	Lemur, Nutch

There are basically three types of search engines: Those that are powered by robots (called crawlers; ants or spiders) and those that are powered by human submissions; and those that are a hybrid of the two.

Crawler-based search engines are those that use automated software agents (called crawlers) that visit a Web site, read the information on the actual site, read the site's meta tags and also follow the links that the site connects to performing indexing on all linked Web sites as well. The crawler returns all that information back to a central depository, where the data is indexed. The crawler will periodically return to the sites to check for any information that has changed. The frequency with which this happens is determined by the administrators of the search engine.

Human-powered search engines rely on humans to submit information that is subsequently indexed and catalogued. Only information that is submitted is put into the index.

In both cases, when you query a search engine to locate information, you're actually searching through the index that the search engine has created —you are not actually searching the Web. These indices are giant databases of information that is collected and stored and subsequently searched. This explains why sometimes a search on a commercial search engine, such as Yahoo! or Google, will return results that are, in fact, dead links. Since the search results are based on the index, if the index has not been updated since a Web page became invalid the search engine treats the page as still an active link even though it no longer is. It will remain that way until the index is updated.

So why will the same search on different search engines produce different results? Part of the answer to that question is because not all indices are going to be exactly the same. It depends on what the spiders find or what the humans submitted. But more important, not every search engine uses the same algorithm to search through the indices. The algorithm is what the search engines use to determine the relevance of the information in the index to what the user is searching for.

One of the elements that a search engine algorithm scans for is the frequency and location of keywords on a Web page. Those with higher frequency are typically considered more relevant. But search engine technology is becoming sophisticated in its attempt to discourage what is known as keyword stuffing, or spamdexing.

Another common element that algorithms analyze is the way that pages link to other pages in the Web. By analyzing how pages link to each other, an engine can both determine what a page is about (if the keywords of the linked pages are similar to the keywords on the original page) and whether that page is considered "important" and deserving of a boost in ranking. Just as the technology is becoming increasingly sophisticated to ignore keyword stuffing, it is also becoming more savvy to Web masters who build artificial links into their sites in order to build an artificial ranking.

Modern web search engines are highly intricate software systems that employ technology that has evolved over the years. There are a number of sub-categories of search engine software that are separately applicable to specific 'browsing' needs. These include web search engines (e.g.

, utilize hundreds of thousands computers to process trillions of web pages in order to return fairly well-aimed results. Due to this high volume of queries and text processing, the software is required to run in a highly dispersed environment with a high degree of superfluity.

Another category of search engines is scientific search engines. These are search engines which search scientific literature. The best known example is Google Scholar. Researchers are working on improving search engine technology by making them understand the content element of the articles, such as extracting theoretical constructs or key research findings.^[74]

Further reading

• Steve Lawrence; C. Lee Giles (1999). "Accessibility of information on the web".
  S2CID 4347646
  .
• Bing Liu (2007), Web Data Mining: Exploring Hyperlinks, Contents and Usage Data. Springer,
  ISBN 3-540-37881-2
• Bar-Ilan, J. (2004). The use of Web search engines in information science research. ARIST, 38, 231–288.
• Levene, Mark (2005). An Introduction to Search Engines and Web Navigation. Pearson.
• Hock, Randolph (2007). The Extreme Searcher's Handbook.
  ISBN 978-0-910965-76-7
• Javed Mostafa (February 2005). "Seeking Better Web Searches".
  doi:10.1038/scientificamerican0205-66
  .
• Ross, Nancy; Wolfram, Dietmar (2000). "End user searching on the Internet: An analysis of term pair topics submitted to the Excite search engine". Journal of the American Society for Information Science. 51 (10): 949–958.
  doi:10.1002/1097-4571(2000)51:10<949::AID-ASI70>3.0.CO;2-5
  .
• Xie, M.; et al. (1998). "Quality dimensions of Internet search engines". Journal of Information Science. 24 (5): 365–372.
  S2CID 34686531
  .
• Information Retrieval: Implementing and Evaluating Search Engines. MIT Press. 2010. Archived from the original on 5 October 2020. Retrieved 7 August 2010.
• Yeo, ShinJoung. (2023) Behind the Search Box: Google and the Global Internet Industry (U of Illinois Press, 2023) ISBN 10:0252087127 online

External links

Wikimedia Commons has media related to Internet search engines.

Wikiversity has learning resources about Search Engines